MADHURA SHRIKRISHNA BUCHAKE **** Woodmar Drive

Contact no: +1-906-***-**** E-mail: ac7w2s@r.postjobfree.com www.linkedin.com/in/madhurabuchake Houghton, MI 49931

Highlights

Experienced Professional with 2.8 years in Data Analytics. Highly skilled in Machine Learning, Data Visualization, Regression models, Statistical Analysis, Statistical methods, Data Mining and Artificial Intelligence.

Educational Qualifications

Master’s in Data Science Michigan Technological University Expected May’19

Bachelor of Engineering in Information Technology University of Pune, India August’10-May’14

Work Experience

Syntel Limited Data Analyst FedEx SmartPost Project September’14-May’17

Developed time-saving Automation tools which increased the efficiency of script execution 9 times that of earlier one using Python and MySQL in Cucumber in an Agile environment leading to 25% increase in profit over 6 months.

Collected, processed, and cleaned data from large FedEx data set using SQL, R, Python, and other scripting and statistical tools.

Gathered business requirements for formulating the Test Plan documentation and Data Preparation.

Collaborated with BA’s, developers and architects in processing the data and transforming into analytic dashboards and workbooks in Tableau reflecting usability, best practices, and current design trends.

Partnered with account to identify metrics that drive performance and used SQL statements, views, stored procedures for data retrieval, manipulation and analysis. Monitored key performance metrics, understanding root causes of changes.

Projects

1Regression using TensorFlow Jun’18-Aug’18

Performed Regression on California Housing Data set using Tensorflow.

Created the estimator model using CNN, RNN, GAN approaches for 3 layers with 8 neurons and approximated the median house value from the values of the rest of the variables.

2Customer Segmentation made on an E-commerce platform Feb’18-Apr’18

Analyzed the content of an E-commerce Database that lists purchases made by ~4000 customers over a period of one year.

Compared the results by applying SVC, Logistic Regression, KNN, Decision Tree, Random Forest, AdaBoost, Gradient Boosting Classifier to anticipate purchases made by a customer, from its first purchase.

Visualized the results using matplot, seaborn, wordcloud. Developed the model using Python.

3Hadoop-MapReduce July’18-Aug’18

Performed analysis on the Uber Datasets in Hadoop using MapReduce in Python and predicted the number of days on which each basement had more trips; and the days on which each basement had a greater number of active vehicles.

4Predicting whether a song will reach the Top10 of Billboard’s Hot 100 Chart Jan’18-Mar’18

Predicted whether a song will make the Top10 of Billboard’s Hot 100 Chart using Machine Learning models.

The best model improved the prediction accuracy of baseline model by over 20%. Implemented in R and Python.

5Statistical Analysis Oct’17-Dec’17

Used Multiple regression model based on hypothesis testing and ANOVA for the Cancer-Smoke dataset to figure out which type of cancer needs to be controlled to reduce death rate of people.

6Data Visualization Apr’18-Jun’18

Worked on Global Burden of diseases Dataset which helped me to find out the causes of the deaths across the globe.

Used advanced visualization techniques like parallel coordinates, heatmaps, treemap etc. to derive some insights on points like: Overall deaths from 1970-2010, Frequency distribution of Number of Deaths across age groups, trend of death rate in different age groups, correlation between different variables, etc. in Python, Tableau, PowerBI and R.

Technical Skills

Machine Learning: Recommendation system Forecasting Feature selection Predictive Modeling

Statistical Techniques: Regression analysis Classification Resampling Methods Hypothesis Testing Time series analysis Dimensionality Reduction.

Software and Programming Languages: Python (scikit-learn, Numpy, SciPy, Pandas, Matplotlib, Plotly, dplyr, ggplot2) R SQL Oracle Proficient with Microsoft Excel LaTeX C C++ Tableau PowerBI

Proficient at: SQL, R, Statistics and Optimization techniques, Data Extraction, Cleaning, Analysis and Presentation

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